merge dev into two_edges
This commit is contained in:
cristhianzl
commit
fcf4512210
133 changed files with 2534 additions and 1507 deletions
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@ -184,7 +184,7 @@ async def build_vertex(
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result_data_response = ResultDataResponse.model_validate(result_dict, from_attributes=True)
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except Exception as exc:
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logger.exception(f"Error building vertex: {exc}")
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logger.exception(f"Error building Component: {exc}")
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params = format_exception_message(exc)
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valid = False
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output_label = vertex.outputs[0]["name"] if vertex.outputs else "output"
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@ -241,7 +241,7 @@ async def build_vertex(
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)
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return build_response
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except Exception as exc:
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logger.error(f"Error building vertex: {exc}")
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logger.error(f"Error building Component: {exc}")
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logger.exception(exc)
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message = parse_exception(exc)
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raise HTTPException(status_code=500, detail=message) from exc
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@ -336,7 +336,7 @@ async def build_vertex_stream(
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raise ValueError(f"No result found for vertex {vertex_id}")
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except Exception as exc:
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logger.exception(f"Error building vertex: {exc}")
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logger.exception(f"Error building Component: {exc}")
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exc_message = parse_exception(exc)
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if exc_message == "The message must be an iterator or an async iterator.":
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exc_message = "This stream has already been closed."
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@ -347,4 +347,4 @@ async def build_vertex_stream(
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return StreamingResponse(stream_vertex(), media_type="text/event-stream")
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except Exception as exc:
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raise HTTPException(status_code=500, detail="Error building vertex") from exc
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raise HTTPException(status_code=500, detail="Error building Component") from exc
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@ -5,9 +5,6 @@ from uuid import UUID
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import sqlalchemy as sa
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from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException, Request, UploadFile, status
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from loguru import logger
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from sqlmodel import Session, select
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from langflow.api.utils import update_frontend_node_with_template_values
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from langflow.api.v1.schemas import (
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ConfigResponse,
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@ -41,6 +38,8 @@ from langflow.services.deps import (
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)
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from langflow.services.session.service import SessionService
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from langflow.services.task.service import TaskService
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from loguru import logger
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from sqlmodel import Session, select
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if TYPE_CHECKING:
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from langflow.services.cache.base import CacheService
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@ -71,29 +70,20 @@ async def get_all(
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async def simple_run_flow(
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db: Session,
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flow: Flow,
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input_request: SimplifiedAPIRequest,
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session_service: SessionService,
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stream: bool = False,
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api_key_user: Optional[User] = None,
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):
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try:
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task_result: List[RunOutputs] = []
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artifacts = {}
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user_id = api_key_user.id if api_key_user else None
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flow_id_str = str(flow.id)
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if input_request.session_id:
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session_data = await session_service.load_session(input_request.session_id, flow_id=flow_id_str)
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graph, artifacts = session_data if session_data else (None, None)
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if graph is None:
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raise ValueError(f"Session {input_request.session_id} not found")
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else:
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if flow.data is None:
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raise ValueError(f"Flow {flow_id_str} has no data")
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graph_data = flow.data
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graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
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graph = Graph.from_payload(graph_data, flow_id=flow_id_str, user_id=str(user_id))
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if flow.data is None:
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raise ValueError(f"Flow {flow_id_str} has no data")
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graph_data = flow.data.copy()
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graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream)
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graph = Graph.from_payload(graph_data, flow_id=flow_id_str, user_id=str(user_id))
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inputs = [
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InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type)
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]
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@ -115,8 +105,6 @@ async def simple_run_flow(
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session_id=input_request.session_id,
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inputs=inputs,
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outputs=outputs,
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artifacts=artifacts,
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session_service=session_service,
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stream=stream,
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)
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@ -189,10 +177,8 @@ async def simplified_run_flow(
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"""
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try:
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return await simple_run_flow(
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db=db,
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flow=flow,
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input_request=input_request,
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session_service=session_service,
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stream=stream,
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api_key_user=api_key_user,
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)
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@ -263,7 +249,6 @@ async def webhook_run_flow(
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db=db,
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flow=flow,
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input_request=input_request,
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session_service=session_service,
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)
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return {"message": "Task started in the background", "status": "in progress"}
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except Exception as exc:
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@ -542,3 +527,4 @@ def get_config():
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except Exception as exc:
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logger.exception(exc)
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raise HTTPException(status_code=500, detail=str(exc)) from exc
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raise HTTPException(status_code=500, detail=str(exc)) from exc
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@ -1,5 +1,7 @@
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from typing import List
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from loguru import logger
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from langflow.graph.schema import ResultData, RunOutputs
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from langflow.schema import Data
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@ -37,9 +39,32 @@ def build_data_from_result_data(result_data: ResultData, get_final_results_only:
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"""
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messages = result_data.messages
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if not messages:
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return []
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data = []
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# Handle results without chat messages (calling flow)
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if not messages:
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# Result with a single record
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if isinstance(result_data.artifacts, dict):
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data.append(Data(data=result_data.artifacts))
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# List of artifacts
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elif isinstance(result_data.artifacts, list):
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for artifact in result_data.artifacts:
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# If multiple records are found as artifacts, return as-is
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if isinstance(artifact, Data):
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data.append(artifact)
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else:
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# Warn about unknown output type
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logger.warning(f"Unable to build record output from unknown ResultData.artifact: {str(artifact)}")
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# Chat or text output
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elif result_data.results:
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data.append(Data(data={"result": result_data.results}, text_key="result"))
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return data
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else:
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return []
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for message in messages:
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message_dict = message if isinstance(message, dict) else message.model_dump()
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if get_final_results_only:
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@ -89,6 +89,7 @@ class AstraDBMessageWriterComponent(BaseMemoryComponent):
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sender_name=sender_name,
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metadata=metadata,
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session_id=session_id,
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type=sender,
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)
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]
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@ -164,4 +164,3 @@ class AstraDBVectorStoreComponent(CustomComponent):
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)
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return vector_store
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return vector_store
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@ -21,6 +21,7 @@ from langflow.type_extraction.type_extraction import (
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extract_union_types_from_generic_alias,
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)
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from langflow.utils import validate
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from pydantic import BaseModel
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if TYPE_CHECKING:
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from langflow.graph.graph.base import Graph
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@ -5,8 +5,6 @@ from functools import partial
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from itertools import chain
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from typing import TYPE_CHECKING, Callable, Coroutine, Dict, Generator, List, Optional, Tuple, Type, Union
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from loguru import logger
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from langflow.graph.edge.base import ContractEdge
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from langflow.graph.graph.constants import lazy_load_vertex_dict
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from langflow.graph.graph.runnable_vertices_manager import RunnableVerticesManager
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@ -21,6 +19,7 @@ from langflow.services.cache.utils import CacheMiss
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from langflow.services.chat.service import ChatService
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from langflow.services.deps import get_chat_service
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from langflow.services.monitor.utils import log_transaction
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from loguru import logger
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if TYPE_CHECKING:
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from langflow.graph.schema import ResultData
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@ -729,6 +728,7 @@ class Graph:
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files: Optional[list[str]] = None,
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user_id: Optional[str] = None,
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fallback_to_env_vars: bool = False,
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cache: bool = True,
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):
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"""
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Builds a vertex in the graph.
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@ -784,19 +784,23 @@ class Graph:
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raise ValueError(f"No result found for vertex {vertex_id}")
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set_cache_coro = partial(chat_service.set_cache, key=self.flow_id)
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next_runnable_vertices, top_level_vertices = await self.get_next_and_top_level_vertices(
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lock, set_cache_coro, vertex
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lock, set_cache_coro, vertex, cache=cache
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)
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flow_id = self.flow_id
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log_transaction(flow_id, vertex, status="success")
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return next_runnable_vertices, top_level_vertices, result_dict, params, valid, artifacts, vertex
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except Exception as exc:
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logger.exception(f"Error building vertex: {exc}")
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logger.exception(f"Error building Component: {exc}")
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flow_id = self.flow_id
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log_transaction(flow_id, vertex, status="failure", error=str(exc))
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raise exc
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async def get_next_and_top_level_vertices(
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self, lock: asyncio.Lock, set_cache_coro: Callable[["Graph", asyncio.Lock], Coroutine], vertex: Vertex
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self,
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lock: asyncio.Lock,
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set_cache_coro: Callable[["Graph", asyncio.Lock], Coroutine],
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vertex: Vertex,
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cache: bool = True,
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):
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"""
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Retrieves the next runnable vertices and the top level vertices for a given vertex.
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@ -809,7 +813,9 @@ class Graph:
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Returns:
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Tuple[List[Vertex], List[Vertex]]: A tuple containing the next runnable vertices and the top level vertices.
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"""
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next_runnable_vertices = await self.run_manager.get_next_runnable_vertices(lock, set_cache_coro, self, vertex)
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next_runnable_vertices = await self.run_manager.get_next_runnable_vertices(
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lock, set_cache_coro, self, vertex, cache=cache
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)
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top_level_vertices = self.run_manager.get_top_level_vertices(self, next_runnable_vertices)
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return next_runnable_vertices, top_level_vertices
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@ -850,13 +856,13 @@ class Graph:
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chat_service = get_chat_service()
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run_id = uuid.uuid4()
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self.set_run_id(run_id)
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lock = chat_service._cache_locks[self.run_id]
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while to_process:
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current_batch = list(to_process) # Copy current deque items to a list
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to_process.clear() # Clear the deque for new items
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tasks = []
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for vertex_id in current_batch:
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vertex = self.get_vertex(vertex_id)
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lock = chat_service._cache_locks[self.run_id]
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task = asyncio.create_task(
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self.build_vertex(
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lock=lock,
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@ -865,6 +871,7 @@ class Graph:
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user_id=self.user_id,
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inputs_dict={},
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fallback_to_env_vars=fallback_to_env_vars,
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cache=False,
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),
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name=f"{vertex.display_name} Run {vertex_task_run_count.get(vertex_id, 0)}",
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)
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@ -872,8 +879,15 @@ class Graph:
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vertex_task_run_count[vertex_id] = vertex_task_run_count.get(vertex_id, 0) + 1
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logger.debug(f"Running layer {layer_index} with {len(tasks)} tasks")
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next_runnable_vertices = await self._execute_tasks(tasks)
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try:
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next_runnable_vertices = await self._execute_tasks(tasks)
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except Exception as e:
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logger.error(f"Error executing tasks in layer {layer_index}: {e}")
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break
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if not next_runnable_vertices:
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break
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to_process.extend(next_runnable_vertices)
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layer_index += 1
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logger.debug("Graph processing complete")
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return self
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@ -881,25 +895,23 @@ class Graph:
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async def _execute_tasks(self, tasks: List[asyncio.Task]) -> List[str]:
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"""Executes tasks in parallel, handling exceptions for each task."""
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results = []
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for i, task in enumerate(asyncio.as_completed(tasks)):
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try:
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result = await task
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if isinstance(result, tuple) and len(result) == 7:
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# Get the next runnable vertices
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next_runnable_vertices = result[0]
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results.extend(next_runnable_vertices)
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else:
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raise ValueError(f"Invalid result: {result}")
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except Exception as e:
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# Log the exception along with the task name for easier debugging
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# task_name = task.get_name()
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# coroutine has not attribute get_name
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task_name = tasks[i].get_name()
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logger.error(f"Task {task_name} failed with exception: {e}")
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completed_tasks = await asyncio.gather(*tasks, return_exceptions=True)
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for i, result in enumerate(completed_tasks):
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task_name = tasks[i].get_name()
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if isinstance(result, Exception):
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logger.error(f"Task {task_name} failed with exception: {result}")
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# Cancel all remaining tasks
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for t in tasks[i:]:
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for t in tasks[i + 1 :]:
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t.cancel()
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raise e
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raise result
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elif isinstance(result, tuple) and len(result) == 7:
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# Get the next runnable vertices
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next_runnable_vertices = result[0]
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results.extend(next_runnable_vertices)
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else:
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raise ValueError(f"Invalid result from task {task_name}: {result}")
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return results
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def topological_sort(self) -> List[Vertex]:
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@ -1377,3 +1389,5 @@ class Graph:
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predecessor_map[edge.target_id].append(edge.source_id)
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successor_map[edge.source_id].append(edge.target_id)
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return predecessor_map, successor_map
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return predecessor_map, successor_map
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return predecessor_map, successor_map
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|
|
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@ -59,6 +59,7 @@ class RunnableVerticesManager:
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set_cache_coro: Callable[["Graph", asyncio.Lock], Awaitable[None]],
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graph: "Graph",
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vertex: "Vertex",
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cache: bool = True,
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):
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"""
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Retrieves the next runnable vertices in the graph for a given vertex.
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@ -86,7 +87,8 @@ class RunnableVerticesManager:
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for v_id in set(next_runnable_vertices): # Use set to avoid duplicates
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self.update_vertex_run_state(v_id, is_runnable=False)
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self.remove_from_predecessors(v_id)
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await set_cache_coro(data=graph, lock=lock) # type: ignore
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if cache:
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await set_cache_coro(data=graph, lock=lock) # type: ignore
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return next_runnable_vertices
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@staticmethod
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|
|
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@ -73,6 +73,7 @@ INPUT_COMPONENTS = [
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OUTPUT_COMPONENTS = [
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InterfaceComponentTypes.ChatOutput,
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InterfaceComponentTypes.TextOutput,
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InterfaceComponentTypes.DataOutput,
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]
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|
|
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|
@ -8,12 +8,16 @@
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"dataType": "OpenAIModel",
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"id": "OpenAIModel-k39HS",
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"name": "text_output",
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"output_types": ["Text"]
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"output_types": [
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"Text"
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]
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},
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"targetHandle": {
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"fieldName": "input_value",
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"id": "ChatOutput-njtka",
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"inputTypes": ["Text", "Message"],
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"inputTypes": [
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"Text"
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],
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"type": "str"
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}
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},
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@ -24,7 +28,7 @@
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"stroke": "#555"
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},
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"target": "ChatOutput-njtka",
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-njtkaœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
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"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-njtkaœ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
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},
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{
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"className": "stroke-gray-900 stroke-connection",
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@ -33,12 +37,18 @@
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"dataType": "Prompt",
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"id": "Prompt-uxBqP",
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"name": "prompt",
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"output_types": ["Prompt"]
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"output_types": [
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"Prompt"
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]
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},
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"targetHandle": {
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"fieldName": "input_value",
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"id": "OpenAIModel-k39HS",
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"inputTypes": ["Text", "Data", "Prompt"],
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"inputTypes": [
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"Text",
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"Data",
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"Prompt"
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],
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"type": "str"
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}
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},
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|
|
@ -58,12 +68,19 @@
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"dataType": "ChatInput",
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"id": "ChatInput-P3fgL",
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"name": "message",
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"output_types": ["Message"]
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"output_types": [
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"Message"
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]
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},
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"targetHandle": {
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"fieldName": "user_input",
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"id": "Prompt-uxBqP",
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"inputTypes": ["Document", "Message", "Record", "Text"],
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"inputTypes": [
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"Document",
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"Message",
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"Record",
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"Text"
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||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -84,10 +101,16 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-uxBqP",
|
||||
"node": {
|
||||
"base_classes": ["object", "str", "Text"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"template": ["user_input"]
|
||||
"template": [
|
||||
"user_input"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -110,7 +133,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -119,7 +144,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -150,7 +177,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -171,7 +200,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Record", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -209,7 +243,11 @@
|
|||
"display_name": "OpenAI",
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"node": {
|
||||
"base_classes": ["object", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -247,7 +285,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -256,7 +296,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -278,7 +320,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -287,7 +329,11 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -307,7 +353,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -327,7 +375,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -347,7 +397,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -373,8 +425,10 @@
|
|||
"dynamic": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": ["Text"],
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -394,7 +448,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": true,
|
||||
"multiline": false,
|
||||
|
|
@ -414,7 +470,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -434,7 +492,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "System message to pass to the model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -454,7 +514,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -490,7 +552,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-njtka",
|
||||
"node": {
|
||||
"base_classes": ["Record", "Text", "str", "object"],
|
||||
"base_classes": [
|
||||
"Record",
|
||||
"Text",
|
||||
"str",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -515,7 +582,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -537,7 +617,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -546,7 +626,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -566,12 +648,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -587,7 +674,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -607,7 +696,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -643,7 +734,12 @@
|
|||
"data": {
|
||||
"id": "ChatInput-P3fgL",
|
||||
"node": {
|
||||
"base_classes": ["object", "Record", "str", "Text"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Record",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -667,7 +763,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -689,7 +798,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, (Message, str)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\nfrom langflow.field_typing import Text\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -718,12 +827,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -739,7 +853,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -759,7 +875,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -803,4 +921,4 @@
|
|||
"is_component": false,
|
||||
"last_tested_version": "1.0.0a4",
|
||||
"name": "Basic Prompting (Hello, World)"
|
||||
}
|
||||
}
|
||||
|
|
@ -13,7 +13,12 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "reference_2",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -34,12 +39,16 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-gi29P",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-JPlxl",
|
||||
"inputTypes": ["Text", "Message"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -50,7 +59,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "ChatOutput-JPlxl",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-JPlxlœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-JPlxlœ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -64,7 +73,12 @@
|
|||
"targetHandle": {
|
||||
"fieldName": "reference_1",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -84,12 +98,19 @@
|
|||
"dataType": "TextInput",
|
||||
"id": "TextInput-og8Or",
|
||||
"name": "Text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "instructions",
|
||||
"id": "Prompt-Rse03",
|
||||
"inputTypes": ["Document", "BaseOutputParser", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -109,12 +130,18 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-Rse03",
|
||||
"name": "prompt",
|
||||
"output_types": ["Prompt"]
|
||||
"output_types": [
|
||||
"Prompt"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-gi29P",
|
||||
"inputTypes": ["Text", "Data", "Prompt"],
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -136,10 +163,18 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-Rse03",
|
||||
"node": {
|
||||
"base_classes": ["object", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"template": ["reference_1", "reference_2", "instructions"]
|
||||
"template": [
|
||||
"reference_1",
|
||||
"reference_2",
|
||||
"instructions"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -162,7 +197,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -171,7 +208,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -280,7 +319,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -316,7 +357,9 @@
|
|||
"data": {
|
||||
"id": "URL-HYPkR",
|
||||
"node": {
|
||||
"base_classes": ["Record"],
|
||||
"base_classes": [
|
||||
"Record"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"urls": null
|
||||
|
|
@ -336,7 +379,9 @@
|
|||
"method": "fetch_content",
|
||||
"name": "data",
|
||||
"selected": "Data",
|
||||
"types": ["Data"],
|
||||
"types": [
|
||||
"Data"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -358,7 +403,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\nimport re\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> Data:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls)\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n"
|
||||
"value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\nimport re\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> Data:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n"
|
||||
},
|
||||
"urls": {
|
||||
"advanced": false,
|
||||
|
|
@ -398,7 +443,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-JPlxl",
|
||||
"node": {
|
||||
"base_classes": ["Text", "Record", "object", "str"],
|
||||
"base_classes": [
|
||||
"Text",
|
||||
"Record",
|
||||
"object",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -423,7 +473,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -445,7 +508,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -454,7 +517,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -474,12 +539,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -495,7 +565,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -515,7 +587,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -546,7 +620,11 @@
|
|||
"data": {
|
||||
"id": "OpenAIModel-gi29P",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -584,7 +662,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -593,7 +673,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -615,7 +697,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -624,7 +706,11 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -644,7 +730,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -664,7 +752,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -684,7 +774,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -710,8 +802,10 @@
|
|||
"dynamic": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": ["Text"],
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -731,7 +825,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": true,
|
||||
"multiline": false,
|
||||
|
|
@ -751,7 +847,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -771,7 +869,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "System message to pass to the model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -791,7 +891,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -827,7 +929,9 @@
|
|||
"data": {
|
||||
"id": "URL-2cX90",
|
||||
"node": {
|
||||
"base_classes": ["Record"],
|
||||
"base_classes": [
|
||||
"Record"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"urls": null
|
||||
|
|
@ -847,7 +951,9 @@
|
|||
"method": "fetch_content",
|
||||
"name": "data",
|
||||
"selected": "Data",
|
||||
"types": ["Data"],
|
||||
"types": [
|
||||
"Data"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -869,7 +975,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\nimport re\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> Data:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls)\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n"
|
||||
"value": "from langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.inputs import StrInput\nfrom langflow.schema import Data\nfrom langflow.template import Output\n\nimport re\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n StrInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n value=\"\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> Data:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(content=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n"
|
||||
},
|
||||
"urls": {
|
||||
"advanced": false,
|
||||
|
|
@ -909,7 +1015,11 @@
|
|||
"data": {
|
||||
"id": "TextInput-og8Or",
|
||||
"node": {
|
||||
"base_classes": ["object", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -922,12 +1032,16 @@
|
|||
"field_order": [],
|
||||
"frozen": false,
|
||||
"icon": "type",
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "Text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"]
|
||||
"types": [
|
||||
"Text"
|
||||
]
|
||||
}
|
||||
],
|
||||
"template": {
|
||||
|
|
@ -957,7 +1071,10 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Text or Record to be passed as input.",
|
||||
"input_types": ["Record", "Text"],
|
||||
"input_types": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -977,7 +1094,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -1021,4 +1140,4 @@
|
|||
"is_component": false,
|
||||
"last_tested_version": "1.0.0a0",
|
||||
"name": "Blog Writer"
|
||||
}
|
||||
}
|
||||
|
|
@ -7,12 +7,19 @@
|
|||
"dataType": "File",
|
||||
"id": "File-BzIs2",
|
||||
"name": "data",
|
||||
"output_types": ["Data"]
|
||||
"output_types": [
|
||||
"Data"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "Document",
|
||||
"id": "Prompt-9DNZG",
|
||||
"inputTypes": ["Document", "Message", "Data", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Data",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -28,12 +35,19 @@
|
|||
"dataType": "ChatInput",
|
||||
"id": "ChatInput-27Usy",
|
||||
"name": "message",
|
||||
"output_types": ["Message"]
|
||||
"output_types": [
|
||||
"Message"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "Question",
|
||||
"id": "Prompt-9DNZG",
|
||||
"inputTypes": ["Document", "Message", "Data", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Data",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -49,12 +63,18 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-9DNZG",
|
||||
"name": "prompt",
|
||||
"output_types": ["Prompt"]
|
||||
"output_types": [
|
||||
"Prompt"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-8b6nG",
|
||||
"inputTypes": ["Text", "Data", "Prompt"],
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -70,12 +90,16 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-8b6nG",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-y4SCS",
|
||||
"inputTypes": ["Text", "Message"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -83,7 +107,7 @@
|
|||
"source": "OpenAIModel-8b6nG",
|
||||
"sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-8b6nGœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œTextœ]}",
|
||||
"target": "ChatOutput-y4SCS",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-y4SCSœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-y4SCSœ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
|
||||
}
|
||||
],
|
||||
"nodes": [
|
||||
|
|
@ -93,11 +117,18 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-9DNZG",
|
||||
"node": {
|
||||
"base_classes": ["object", "str", "Text"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"conditional_paths": [],
|
||||
"custom_fields": {
|
||||
"template": ["Document", "Question"]
|
||||
"template": [
|
||||
"Document",
|
||||
"Question"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -119,7 +150,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -128,7 +161,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -142,7 +177,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Data", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Data",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -163,7 +203,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Data", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Data",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -202,7 +247,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -238,7 +285,12 @@
|
|||
"data": {
|
||||
"id": "ChatInput-27Usy",
|
||||
"node": {
|
||||
"base_classes": ["str", "Record", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Record",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -262,7 +314,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -284,7 +349,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, (Message, str)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\nfrom langflow.field_typing import Text\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -313,12 +378,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -334,7 +404,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -354,7 +426,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -390,7 +464,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-y4SCS",
|
||||
"node": {
|
||||
"base_classes": ["str", "Record", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Record",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -414,7 +493,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -436,7 +528,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -445,7 +537,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -465,12 +559,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -486,7 +585,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -506,7 +607,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -544,7 +647,9 @@
|
|||
"display_name": "File",
|
||||
"id": "File-BzIs2",
|
||||
"node": {
|
||||
"base_classes": ["Data"],
|
||||
"base_classes": [
|
||||
"Data"
|
||||
],
|
||||
"beta": false,
|
||||
"conditional_paths": [],
|
||||
"custom_fields": {},
|
||||
|
|
@ -552,7 +657,10 @@
|
|||
"display_name": "File",
|
||||
"documentation": "",
|
||||
"edited": true,
|
||||
"field_order": ["path", "silent_errors"],
|
||||
"field_order": [
|
||||
"path",
|
||||
"silent_errors"
|
||||
],
|
||||
"frozen": false,
|
||||
"icon": "file-text",
|
||||
"output_types": [],
|
||||
|
|
@ -563,7 +671,9 @@
|
|||
"method": "load_file",
|
||||
"name": "data",
|
||||
"selected": "Data",
|
||||
"types": ["Data"],
|
||||
"types": [
|
||||
"Data"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -660,7 +770,10 @@
|
|||
"data": {
|
||||
"id": "OpenAIModel-8b6nG",
|
||||
"node": {
|
||||
"base_classes": ["BaseLanguageModel", "Text"],
|
||||
"base_classes": [
|
||||
"BaseLanguageModel",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"conditional_paths": [],
|
||||
"custom_fields": {},
|
||||
|
|
@ -688,7 +801,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -697,7 +812,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -720,14 +837,18 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
"display_name": "Input",
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"name": "input_value",
|
||||
|
|
@ -788,7 +909,7 @@
|
|||
"advanced": true,
|
||||
"display_name": "OpenAI API Base",
|
||||
"dynamic": false,
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"name": "openai_api_base",
|
||||
|
|
@ -804,7 +925,9 @@
|
|||
"display_name": "OpenAI API Key",
|
||||
"dynamic": false,
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"load_from_db": true,
|
||||
"name": "openai_api_key",
|
||||
"password": true,
|
||||
|
|
@ -889,4 +1012,4 @@
|
|||
"is_component": false,
|
||||
"last_tested_version": "1.0.0a52",
|
||||
"name": "Document QA"
|
||||
}
|
||||
}
|
||||
|
|
@ -8,12 +8,19 @@
|
|||
"dataType": "MemoryComponent",
|
||||
"id": "MemoryComponent-cdA1J",
|
||||
"name": "text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "context",
|
||||
"id": "Prompt-ODkUx",
|
||||
"inputTypes": ["Document", "Message", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -34,12 +41,19 @@
|
|||
"dataType": "ChatInput",
|
||||
"id": "ChatInput-t7F8v",
|
||||
"name": "message",
|
||||
"output_types": ["Message"]
|
||||
"output_types": [
|
||||
"Message"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "user_message",
|
||||
"id": "Prompt-ODkUx",
|
||||
"inputTypes": ["Document", "Message", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -60,12 +74,18 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-ODkUx",
|
||||
"name": "prompt",
|
||||
"output_types": ["Prompt"]
|
||||
"output_types": [
|
||||
"Prompt"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-9RykF",
|
||||
"inputTypes": ["Text", "Data", "Prompt"],
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -85,12 +105,16 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-9RykF",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-P1jEe",
|
||||
"inputTypes": ["Text", "Message"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -101,7 +125,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "ChatOutput-P1jEe",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-P1jEeœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-P1jEeœ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-foreground stroke-connection",
|
||||
|
|
@ -110,12 +134,17 @@
|
|||
"dataType": "MemoryComponent",
|
||||
"id": "MemoryComponent-cdA1J",
|
||||
"name": "text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "TextOutput-vrs6T",
|
||||
"inputTypes": ["Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -134,7 +163,12 @@
|
|||
"data": {
|
||||
"id": "ChatInput-t7F8v",
|
||||
"node": {
|
||||
"base_classes": ["Text", "object", "Record", "str"],
|
||||
"base_classes": [
|
||||
"Text",
|
||||
"object",
|
||||
"Record",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -158,7 +192,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -180,7 +227,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, (Message, str)) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\nfrom langflow.field_typing import Text\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n input_types=[],\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n StrInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n StrInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -209,12 +256,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -230,7 +282,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -250,7 +304,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -286,7 +342,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-P1jEe",
|
||||
"node": {
|
||||
"base_classes": ["Text", "object", "Record", "str"],
|
||||
"base_classes": [
|
||||
"Text",
|
||||
"object",
|
||||
"Record",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -310,7 +371,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -332,7 +406,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -341,7 +415,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -361,12 +437,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -382,7 +463,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -402,7 +485,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -440,7 +525,11 @@
|
|||
"display_name": "Chat Memory",
|
||||
"id": "MemoryComponent-cdA1J",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": true,
|
||||
"custom_fields": {
|
||||
"n_messages": null,
|
||||
|
|
@ -457,7 +546,9 @@
|
|||
"field_order": [],
|
||||
"frozen": false,
|
||||
"icon": "history",
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"cache": true,
|
||||
|
|
@ -466,7 +557,9 @@
|
|||
"method": null,
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -516,12 +609,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Order of the messages.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "order",
|
||||
"options": ["Ascending", "Descending"],
|
||||
"options": [
|
||||
"Ascending",
|
||||
"Descending"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -537,12 +635,18 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User", "Machine and User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User",
|
||||
"Machine and User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -558,7 +662,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -577,7 +683,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID of the chat history.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -615,10 +723,17 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-ODkUx",
|
||||
"node": {
|
||||
"base_classes": ["Text", "str", "object"],
|
||||
"base_classes": [
|
||||
"Text",
|
||||
"str",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"template": ["context", "user_message"]
|
||||
"template": [
|
||||
"context",
|
||||
"user_message"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -641,7 +756,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -650,7 +767,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -682,7 +801,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Record", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -702,7 +826,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -723,7 +849,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Record", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -759,7 +890,11 @@
|
|||
"data": {
|
||||
"id": "OpenAIModel-9RykF",
|
||||
"node": {
|
||||
"base_classes": ["str", "object", "Text"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"object",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -797,7 +932,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -806,7 +943,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -828,7 +967,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -837,7 +976,11 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -857,7 +1000,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -877,7 +1022,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -897,7 +1044,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -923,8 +1072,10 @@
|
|||
"dynamic": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": ["Text"],
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -944,7 +1095,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": true,
|
||||
"multiline": false,
|
||||
|
|
@ -964,7 +1117,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -984,7 +1139,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "System message to pass to the model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1004,7 +1161,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1040,7 +1199,11 @@
|
|||
"data": {
|
||||
"id": "TextOutput-vrs6T",
|
||||
"node": {
|
||||
"base_classes": ["str", "object", "Text"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"object",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -1053,7 +1216,9 @@
|
|||
"field_order": [],
|
||||
"frozen": false,
|
||||
"icon": "type",
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"template": {
|
||||
"_type": "CustomComponent",
|
||||
"code": {
|
||||
|
|
@ -1081,7 +1246,10 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Text or Record to be passed as output.",
|
||||
"input_types": ["Record", "Text"],
|
||||
"input_types": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1101,7 +1269,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -1147,4 +1317,4 @@
|
|||
"is_component": false,
|
||||
"last_tested_version": "1.0.0a0",
|
||||
"name": "Memory Chatbot"
|
||||
}
|
||||
}
|
||||
|
|
@ -8,12 +8,19 @@
|
|||
"dataType": "TextInput",
|
||||
"id": "TextInput-sptaH",
|
||||
"name": "text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "document",
|
||||
"id": "Prompt-amqBu",
|
||||
"inputTypes": ["Document", "Message", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -33,12 +40,17 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-amqBu",
|
||||
"name": "text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "TextOutput-2MS4a",
|
||||
"inputTypes": ["Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -58,12 +70,18 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-amqBu",
|
||||
"name": "prompt",
|
||||
"output_types": ["Prompt"]
|
||||
"output_types": [
|
||||
"Prompt"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-uYXZJ",
|
||||
"inputTypes": ["Text", "Data", "Prompt"],
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -83,12 +101,19 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-uYXZJ",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "summary",
|
||||
"id": "Prompt-gTNiz",
|
||||
"inputTypes": ["Document", "Message", "Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -108,12 +133,16 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-uYXZJ",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-EJkG3",
|
||||
"inputTypes": ["Text", "Message"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -124,7 +153,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "ChatOutput-EJkG3",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-EJkG3œ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-EJkG3œ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
|
||||
},
|
||||
{
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
|
|
@ -133,12 +162,17 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-gTNiz",
|
||||
"name": "text",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "TextOutput-MUDOR",
|
||||
"inputTypes": ["Record", "Text"],
|
||||
"inputTypes": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -158,12 +192,18 @@
|
|||
"dataType": "Prompt",
|
||||
"id": "Prompt-gTNiz",
|
||||
"name": "prompt",
|
||||
"output_types": ["Prompt"]
|
||||
"output_types": [
|
||||
"Prompt"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-XawYB",
|
||||
"inputTypes": ["Text", "Data", "Prompt"],
|
||||
"inputTypes": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -183,12 +223,16 @@
|
|||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-XawYB",
|
||||
"name": "text_output",
|
||||
"output_types": ["Text"]
|
||||
"output_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-DNmvg",
|
||||
"inputTypes": ["Text", "Message"],
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
|
|
@ -199,7 +243,7 @@
|
|||
"stroke": "#555"
|
||||
},
|
||||
"target": "ChatOutput-DNmvg",
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-DNmvgœ, œinputTypesœ: [œTextœ, œMessageœ], œtypeœ: œstrœ}"
|
||||
"targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-DNmvgœ, œinputTypesœ: [œTextœ], œtypeœ: œstrœ}"
|
||||
}
|
||||
],
|
||||
"nodes": [
|
||||
|
|
@ -209,10 +253,16 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-amqBu",
|
||||
"node": {
|
||||
"base_classes": ["object", "str", "Text"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"template": ["document"]
|
||||
"template": [
|
||||
"document"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -235,7 +285,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -244,7 +296,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -276,7 +330,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Record", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -296,7 +355,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -334,10 +395,16 @@
|
|||
"display_name": "Prompt",
|
||||
"id": "Prompt-gTNiz",
|
||||
"node": {
|
||||
"base_classes": ["object", "str", "Text"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"template": ["summary"]
|
||||
"template": [
|
||||
"summary"
|
||||
]
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt",
|
||||
|
|
@ -360,7 +427,9 @@
|
|||
"method": "build_prompt",
|
||||
"name": "prompt",
|
||||
"selected": "Prompt",
|
||||
"types": ["Prompt"],
|
||||
"types": [
|
||||
"Prompt"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -369,7 +438,9 @@
|
|||
"method": "format_prompt",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -401,7 +472,12 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Document", "Message", "Record", "Text"],
|
||||
"input_types": [
|
||||
"Document",
|
||||
"Message",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -421,7 +497,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -453,7 +531,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-EJkG3",
|
||||
"node": {
|
||||
"base_classes": ["object", "Record", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Record",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -478,7 +561,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -500,7 +596,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -509,7 +605,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -529,12 +627,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -550,7 +653,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -570,7 +675,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -602,7 +709,12 @@
|
|||
"data": {
|
||||
"id": "ChatOutput-DNmvg",
|
||||
"node": {
|
||||
"base_classes": ["object", "Record", "Text", "str"],
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Record",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -627,7 +739,20 @@
|
|||
"method": "message_response",
|
||||
"name": "message",
|
||||
"selected": "Message",
|
||||
"types": ["Message"],
|
||||
"types": [
|
||||
"Message"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
"cache": true,
|
||||
"display_name": "Text",
|
||||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -649,7 +774,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput, DropdownInput, MultilineInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n input_types=[\"Text\", \"Message\"],\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n if isinstance(self.input_value, Message):\n message = self.input_value\n else:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.status = message\n return message\n"
|
||||
"value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import BoolInput, DropdownInput, StrInput\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n StrInput(name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True),\n StrInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n BoolInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n\n def text_response(self) -> Text:\n text = self.message_response().text\n return text\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -658,7 +783,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Message to be passed as output.",
|
||||
"input_types": ["Text", "Message"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -678,12 +805,17 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Type of sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
"name": "sender",
|
||||
"options": ["Machine", "User"],
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"password": false,
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
|
|
@ -699,7 +831,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Name of the sender.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -719,7 +853,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Session ID for the message.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -750,7 +886,11 @@
|
|||
"data": {
|
||||
"id": "TextInput-sptaH",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -771,7 +911,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -793,7 +935,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import MultilineInput, StrInput\nfrom langflow.template import Output\n\n\nclass TextInput(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n MultilineInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n advanced=True,\n value=\"{text}\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Text:\n return self.build(input_value=self.input_value, data_template=self.data_template)\n"
|
||||
"value": "from langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\nfrom langflow.inputs import StrInput\nfrom langflow.template import Output\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n StrInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Text:\n return self.build(input_value=self.input_value)\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -802,7 +944,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Text to be passed as input.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -838,7 +982,11 @@
|
|||
"data": {
|
||||
"id": "TextOutput-2MS4a",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -851,7 +999,9 @@
|
|||
"field_order": [],
|
||||
"frozen": false,
|
||||
"icon": "type",
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"template": {
|
||||
"_type": "CustomComponent",
|
||||
"code": {
|
||||
|
|
@ -879,7 +1029,10 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Text or Record to be passed as output.",
|
||||
"input_types": ["Record", "Text"],
|
||||
"input_types": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -899,7 +1052,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -935,7 +1090,11 @@
|
|||
"data": {
|
||||
"id": "OpenAIModel-uYXZJ",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -973,7 +1132,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -982,7 +1143,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -1004,7 +1167,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -1013,7 +1176,11 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1033,7 +1200,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1053,7 +1222,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1073,7 +1244,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1099,8 +1272,10 @@
|
|||
"dynamic": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": ["Text"],
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1120,7 +1295,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": true,
|
||||
"multiline": false,
|
||||
|
|
@ -1140,7 +1317,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1160,7 +1339,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "System message to pass to the model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1180,7 +1361,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1216,7 +1399,11 @@
|
|||
"data": {
|
||||
"id": "TextOutput-MUDOR",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -1229,7 +1416,9 @@
|
|||
"field_order": [],
|
||||
"frozen": false,
|
||||
"icon": "type",
|
||||
"output_types": ["Text"],
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"template": {
|
||||
"_type": "CustomComponent",
|
||||
"code": {
|
||||
|
|
@ -1257,7 +1446,10 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Text or Record to be passed as output.",
|
||||
"input_types": ["Record", "Text"],
|
||||
"input_types": [
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1277,7 +1469,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": true,
|
||||
|
|
@ -1313,7 +1507,11 @@
|
|||
"data": {
|
||||
"id": "OpenAIModel-XawYB",
|
||||
"node": {
|
||||
"base_classes": ["str", "Text", "object"],
|
||||
"base_classes": [
|
||||
"str",
|
||||
"Text",
|
||||
"object"
|
||||
],
|
||||
"beta": false,
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
|
|
@ -1351,7 +1549,9 @@
|
|||
"method": "text_response",
|
||||
"name": "text_output",
|
||||
"selected": "Text",
|
||||
"types": ["Text"],
|
||||
"types": [
|
||||
"Text"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
},
|
||||
{
|
||||
|
|
@ -1360,7 +1560,9 @@
|
|||
"method": "build_model",
|
||||
"name": "model_output",
|
||||
"selected": "BaseLanguageModel",
|
||||
"types": ["BaseLanguageModel"],
|
||||
"types": [
|
||||
"BaseLanguageModel"
|
||||
],
|
||||
"value": "__UNDEFINED__"
|
||||
}
|
||||
],
|
||||
|
|
@ -1382,7 +1584,7 @@
|
|||
"show": true,
|
||||
"title_case": false,
|
||||
"type": "code",
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, SecretStrInput, StrInput\nfrom langflow.inputs.inputs import IntInput\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n return output\n"
|
||||
"value": "from langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import BaseLanguageModel, Text\nfrom langflow.inputs import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput\nfrom langflow.template import Output\n\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n StrInput(name=\"input_value\", display_name=\"Input\", input_types=[\"Text\", \"Data\", \"Prompt\"]),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n BoolInput(\n name=\"json_mode\",\n display_name=\"JSON Mode\",\n info=\"Enable JSON mode for the model output.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Text:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> BaseLanguageModel:\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = self.json_mode\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n response_format = None\n if json_mode:\n response_format = {\"type\": \"json_object\"}\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name or None,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n response_format=response_format,\n seed=seed,\n )\n\n return output\n"
|
||||
},
|
||||
"input_value": {
|
||||
"advanced": false,
|
||||
|
|
@ -1391,7 +1593,11 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text", "Data", "Prompt"],
|
||||
"input_types": [
|
||||
"Text",
|
||||
"Data",
|
||||
"Prompt"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1411,7 +1617,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1431,7 +1639,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1451,7 +1661,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": true,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1477,8 +1689,10 @@
|
|||
"dynamic": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": ["Text"],
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1498,7 +1712,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": true,
|
||||
"multiline": false,
|
||||
|
|
@ -1518,7 +1734,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1538,7 +1756,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "System message to pass to the model.",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1558,7 +1778,9 @@
|
|||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"info": "",
|
||||
"input_types": ["Text"],
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"list": false,
|
||||
"load_from_db": false,
|
||||
"multiline": false,
|
||||
|
|
@ -1602,4 +1824,4 @@
|
|||
"is_component": false,
|
||||
"last_tested_version": "1.0.0a0",
|
||||
"name": "Prompt Chaining"
|
||||
}
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
|
|
@ -1,15 +1,13 @@
|
|||
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
|
||||
|
||||
from loguru import logger
|
||||
from pydantic import BaseModel
|
||||
|
||||
from langflow.graph.graph.base import Graph
|
||||
from langflow.graph.schema import RunOutputs
|
||||
from langflow.graph.vertex.base import Vertex
|
||||
from langflow.schema.graph import InputValue, Tweaks
|
||||
from langflow.schema.schema import INPUT_FIELD_NAME
|
||||
from langflow.services.deps import get_settings_service
|
||||
from langflow.services.session.service import SessionService
|
||||
from loguru import logger
|
||||
from pydantic import BaseModel
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.api.v1.schemas import InputValueRequest
|
||||
|
|
@ -27,18 +25,13 @@ async def run_graph_internal(
|
|||
session_id: Optional[str] = None,
|
||||
inputs: Optional[List["InputValueRequest"]] = None,
|
||||
outputs: Optional[List[str]] = None,
|
||||
artifacts: Optional[Dict[str, Any]] = None,
|
||||
session_service: Optional[SessionService] = None,
|
||||
) -> tuple[List[RunOutputs], str]:
|
||||
"""Run the graph and generate the result"""
|
||||
inputs = inputs or []
|
||||
graph_data = graph._graph_data
|
||||
if session_id is None and session_service is not None:
|
||||
session_id_str = session_service.generate_key(session_id=flow_id, data_graph=graph_data)
|
||||
elif session_id is not None:
|
||||
session_id_str = session_id
|
||||
if session_id is None:
|
||||
session_id_str = flow_id
|
||||
else:
|
||||
raise ValueError("session_id or session_service must be provided")
|
||||
session_id_str = session_id
|
||||
components = []
|
||||
inputs_list = []
|
||||
types = []
|
||||
|
|
@ -53,16 +46,14 @@ async def run_graph_internal(
|
|||
fallback_to_env_vars = get_settings_service().settings.fallback_to_env_var
|
||||
|
||||
run_outputs = await graph.arun(
|
||||
inputs_list,
|
||||
components,
|
||||
types,
|
||||
outputs or [],
|
||||
inputs=inputs_list,
|
||||
inputs_components=components,
|
||||
types=types,
|
||||
outputs=outputs or [],
|
||||
stream=stream,
|
||||
session_id=session_id_str or "",
|
||||
fallback_to_env_vars=fallback_to_env_vars,
|
||||
)
|
||||
if session_id_str and session_service:
|
||||
await session_service.update_session(session_id_str, (graph, artifacts))
|
||||
return run_outputs, session_id_str
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -4,19 +4,21 @@ from typing import TYPE_CHECKING, List, Optional, Union
|
|||
|
||||
import duckdb
|
||||
from langflow.services.base import Service
|
||||
from langflow.services.monitor.schema import MessageModel, TransactionModel, VertexBuildModel
|
||||
from langflow.services.monitor.utils import add_row_to_table, drop_and_create_table_if_schema_mismatch
|
||||
from loguru import logger
|
||||
from platformdirs import user_cache_dir
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langflow.services.settings.manager import SettingsService
|
||||
from langflow.services.monitor.schema import MessageModel, TransactionModel, VertexBuildModel
|
||||
|
||||
|
||||
class MonitorService(Service):
|
||||
name = "monitor_service"
|
||||
|
||||
def __init__(self, settings_service: "SettingsService"):
|
||||
from langflow.services.monitor.schema import MessageModel, TransactionModel, VertexBuildModel
|
||||
|
||||
self.settings_service = settings_service
|
||||
self.base_cache_dir = Path(user_cache_dir("langflow"))
|
||||
self.db_path = self.base_cache_dir / "monitor.duckdb"
|
||||
|
|
@ -45,7 +47,7 @@ class MonitorService(Service):
|
|||
def add_row(
|
||||
self,
|
||||
table_name: str,
|
||||
data: Union[dict, TransactionModel, MessageModel, VertexBuildModel],
|
||||
data: Union[dict, "TransactionModel", "MessageModel", "VertexBuildModel"],
|
||||
):
|
||||
# Make sure the model passed matches the table
|
||||
|
||||
|
|
@ -127,7 +129,7 @@ class MonitorService(Service):
|
|||
|
||||
return self.exec_query(query, read_only=False)
|
||||
|
||||
def add_message(self, message: MessageModel):
|
||||
def add_message(self, message: "MessageModel"):
|
||||
self.add_row("messages", message)
|
||||
|
||||
def get_messages(
|
||||
|
|
|
|||
55
src/backend/base/poetry.lock
generated
55
src/backend/base/poetry.lock
generated
|
|
@ -337,6 +337,17 @@ files = [
|
|||
[package.dependencies]
|
||||
pycparser = "*"
|
||||
|
||||
[[package]]
|
||||
name = "chardet"
|
||||
version = "5.2.0"
|
||||
description = "Universal encoding detector for Python 3"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"},
|
||||
{file = "chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.3.2"
|
||||
|
|
@ -1158,19 +1169,19 @@ files = [
|
|||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "0.2.4"
|
||||
version = "0.2.5"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain-0.2.4-py3-none-any.whl", hash = "sha256:a04813215c30f944df006031e2febde872af8fab628dcee825d969e07b6cd621"},
|
||||
{file = "langchain-0.2.4.tar.gz", hash = "sha256:e704b5b06222d5eba2d02c76f891321d1bac8952ed54e093831b2bdabf99dcd5"},
|
||||
{file = "langchain-0.2.5-py3-none-any.whl", hash = "sha256:9aded9a65348254e1c93dcdaacffe4d1b6a5e7f74ef80c160c88ff78ad299228"},
|
||||
{file = "langchain-0.2.5.tar.gz", hash = "sha256:ffdbf4fcea46a10d461bcbda2402220fcfd72a0c70e9f4161ae0510067b9b3bd"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
aiohttp = ">=3.8.3,<4.0.0"
|
||||
async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
|
||||
langchain-core = ">=0.2.6,<0.3.0"
|
||||
langchain-core = ">=0.2.7,<0.3.0"
|
||||
langchain-text-splitters = ">=0.2.0,<0.3.0"
|
||||
langsmith = ">=0.1.17,<0.2.0"
|
||||
numpy = [
|
||||
|
|
@ -1185,22 +1196,25 @@ tenacity = ">=8.1.0,<9.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langchain-community"
|
||||
version = "0.2.4"
|
||||
version = "0.2.5"
|
||||
description = "Community contributed LangChain integrations."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_community-0.2.4-py3-none-any.whl", hash = "sha256:8582e9800f4837660dc297cccd2ee1ddc1d8c440d0fe8b64edb07620f0373b0e"},
|
||||
{file = "langchain_community-0.2.4.tar.gz", hash = "sha256:2bb6a1a36b8500a564d25d76469c02457b1a7c3afea6d4a609a47c06b993e3e4"},
|
||||
{file = "langchain_community-0.2.5-py3-none-any.whl", hash = "sha256:bf37a334952e42c7676d083cf2d2c4cbfbb7de1949c4149fe19913e2b06c485f"},
|
||||
{file = "langchain_community-0.2.5.tar.gz", hash = "sha256:476787b8c8c213b67e7b0eceb53346e787f00fbae12d8e680985bd4f93b0bf64"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
aiohttp = ">=3.8.3,<4.0.0"
|
||||
dataclasses-json = ">=0.5.7,<0.7"
|
||||
langchain = ">=0.2.0,<0.3.0"
|
||||
langchain-core = ">=0.2.0,<0.3.0"
|
||||
langchain = ">=0.2.5,<0.3.0"
|
||||
langchain-core = ">=0.2.7,<0.3.0"
|
||||
langsmith = ">=0.1.0,<0.2.0"
|
||||
numpy = ">=1,<2"
|
||||
numpy = [
|
||||
{version = ">=1,<2", markers = "python_version < \"3.12\""},
|
||||
{version = ">=1.26.0,<2.0.0", markers = "python_version >= \"3.12\""},
|
||||
]
|
||||
PyYAML = ">=5.3"
|
||||
requests = ">=2,<3"
|
||||
SQLAlchemy = ">=1.4,<3"
|
||||
|
|
@ -1208,13 +1222,13 @@ tenacity = ">=8.1.0,<9.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.2.6"
|
||||
version = "0.2.7"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_core-0.2.6-py3-none-any.whl", hash = "sha256:90521c9fc95d8f925e0d2e2d952382676aea6d3f8de611eda1b1810874c31e5d"},
|
||||
{file = "langchain_core-0.2.6.tar.gz", hash = "sha256:9f0e38da722a558a6e95b6d86de01bd92e84558c47ac8ba599f02eab70a1c873"},
|
||||
{file = "langchain_core-0.2.7-py3-none-any.whl", hash = "sha256:fd02e153c898486dd728d634684ffc64bc257ff2ba443dc7e53d017ac0bf4658"},
|
||||
{file = "langchain_core-0.2.7.tar.gz", hash = "sha256:b0b1b6dfbdedb39426fcb8bd3f07e40eec7964856e3fc384c420ca6dba61b34e"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -1227,21 +1241,18 @@ tenacity = ">=8.1.0,<9.0.0"
|
|||
|
||||
[[package]]
|
||||
name = "langchain-experimental"
|
||||
version = "0.0.60"
|
||||
version = "0.0.61"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_experimental-0.0.60-py3-none-any.whl", hash = "sha256:ef3b6b6b84fe2bfe19eba6d1a98005e27d96576514c6415f5afe4ace5bf477d8"},
|
||||
{file = "langchain_experimental-0.0.60.tar.gz", hash = "sha256:a16cbcd18cda6b86be8f41fed7963c13569295def0d8b4c6324b806d878d442c"},
|
||||
{file = "langchain_experimental-0.0.61-py3-none-any.whl", hash = "sha256:f9c516f528f55919743bd56fe1689a53bf74ae7f8902d64b9d8aebc61249cbe2"},
|
||||
{file = "langchain_experimental-0.0.61.tar.gz", hash = "sha256:e9538efb994be5db3045cc582cddb9787c8299c86ffeee9d3779b7f58eef2226"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
langchain-community = ">=0.2,<0.3"
|
||||
langchain-core = ">=0.2,<0.3"
|
||||
|
||||
[package.extras]
|
||||
extended-testing = ["faker (>=19.3.1,<20.0.0)", "jinja2 (>=3,<4)", "pandas (>=2.0.1,<3.0.0)", "presidio-analyzer (>=2.2.352,<3.0.0)", "presidio-anonymizer (>=2.2.352,<3.0.0)", "sentence-transformers (>=2,<3)", "tabulate (>=0.9.0,<0.10.0)", "vowpal-wabbit-next (==0.6.0)"]
|
||||
langchain-community = ">=0.2.5,<0.3.0"
|
||||
langchain-core = ">=0.2.7,<0.3.0"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-text-splitters"
|
||||
|
|
@ -3297,4 +3308,4 @@ local = []
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<3.13"
|
||||
content-hash = "72f05330f1e734596d160b45cb68ab2ebf7d0824314bec0566bddb5b2043f4e6"
|
||||
content-hash = "73dc20fcd3c34d40dd31c9251efc8e2d8d3346f2f1bc18be516acf57c86ce460"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow-base"
|
||||
version = "0.0.68"
|
||||
version = "0.0.70"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Langflow <contact@langflow.org>"]
|
||||
maintainers = [
|
||||
|
|
@ -64,6 +64,7 @@ asyncer = "^0.0.5"
|
|||
pyperclip = "^1.8.2"
|
||||
uncurl = "^0.0.11"
|
||||
sentry-sdk = "^2.5.1"
|
||||
chardet = "^5.2.0"
|
||||
|
||||
|
||||
[tool.poetry.extras]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue